tbuckley/cabot-search huggingface dataset:
IMMU-07. THE CXCL16/CXCR6 AXIS REGULATES CD8+ T-CELL RECRUITMENT AND FUNCTION IN GLIOBLASTOMA
Authors: Tzu-Yi Chia, Leah Billingham, Lauren Boland, Hanxiao Wan, Si Wang, Joshua Katz, David Hou, Gustavo Ignacio Vazquez Cervantes, Yu Han, Aurora Lopez-Rosas, Peng Zhang, Catalina Lee-Chang, Jason Miska
Journal: Neuro-Oncology (2023)

Abstract INTRODUCTION Glioblastoma (GBM) is the most common and aggressive primary brain tumor with a poor prognosis and no curative treatment. Immunotherapy, revolutionizing oncology, is currently ineffective for GBM due to the immunosuppressive tumor microenvironment. A critical driver is tumor-associated macrophages (TAMs) infiltration, which is correlated to T-cell deficiency and tumor progression. While the interactions between TAMs and T-cells are known to inhibit the antitumor functions, the mechanisms driving these interactions in GBM are still not established. Our data shows that the CXCL16/CXCR6 axis is likely the predominant chemokine-receptor interaction among TAMs and CD8+ T-cells population in GBM. Understanding the role of this axis is crucial in modulating antitumor immune functions in GBM. METHODS We designed several migration and adhesion assays to determine how the CXCL16/CXCR6 axis influences: CD8+ T-cell migration, TAM: CD8+ T-cell interactions, and CD8+ T-cell dysfunction in GBM. In addition, long-term survival with immune checkpoint treatment was done to understand the influence of the axis on murine tumor growth. RESULTS While CXCR6 deficiency prevented T-cell infiltration into tumors, the CD8+ T-cells cells within the tumors expressed more markers associated with cytotoxicity and exhaustion. Furthermore, CXCR6 deficient CD8+ T cells were less adherent to immunosuppressive TAMs. Importantly, CXCR6 deficiency worked in concert with anti-PD1 to promote tumor rejection in the CT2A tumor-bearing model of GBM. CONCLUSION Our data show that while CXCR6 is crucial in trafficking CD8+ T-cells to tumors from the periphery, it promotes immunosuppressive interactions between TAMs/CD8+ T-cells within tumors. Thus, the CXCR6 axis exerts opposing roles in anti-tumor immunity in GBM.
EPCO-46. CHARACTERIZING ATYPICAL TERATOID RHABDOID TUMOR SUBTYPE ENHANCER INTERACTION LANDSCAPE
Authors: Ben Ho, Xiaolian Fan, Liming Xu, Annie Huang
Journal: Neuro-Oncology (2023)

Abstract Atypical Teratoid Rhabdoid Tumor (ATRT) is one of the most aggressive pediatric tumors of the central nervous system (CNS). The majority of ATRTs are characterized by the recurrent bi-allelic loss of the SWI/SNF nucleosome remodeling complex core component gene, SMARCB1, or SMARCA4 in rare cases. Despite its bland genome, three ATRT subgroups “SHH”, “TYR”, and “MYC” were discovered with unique molecular profiles. Also, distinct activating histone mark H3K27ac profiles between molecular subgroups were identified, suggesting subgroup-specific regulatory networks through enhancers. However, comprehensive cis-regulatory network descriptions in ATRT are lacking. Here, we aim to elucidate ATRT subgroup pathogenesis through its dysregulated enhancer-promoter interactions. We have created a regulatory mutational profile of the three ATRT subgroups using whole-genome sequencing method of 60 ATRT tumors and matching genome-wide H3K27ac profiles on 16 tumors. To investigate mutation burden on cis-regulations, we have employed high-throughput Hi-C chromatin immunoprecipitation (HiChIP) technique to directly map enhancer sequences involved in DNA-looping with high specificity and sensitivity. Recent findings from our lab suggest that activating interaction PDGFRB confer to therapeutics venerability in the MYC subgroup. Here, our preliminary analysis shows a hub of interactions near PDGFRB reveals an extensive interaction hub with long-range enhancer interactions extending as far as 1500Kb, suggesting a much more complicated regulatory picture than previously expected. Interestingly, we have identified long-range DNA interactions between PDGFRB and H3K27ac marks upstream of its gene body and overstretching into other gene elements. This result suggests a potential alternative activation mechanism for MYC cell lines. Our next steps are to perform performing additional HiChIP assays on other ATRT cell lines from other subgroups to capture the full range of ATRT’s heterogeneity. Comprehensive mapping of the non-coding genome and enhancer regulatory network would help identify critical pathogenic elements underlying ATRT biology and provide insights into therapeutic targets.
DDEL-05. PHARMACOKINETIC ASSESSMENT OF CONVECTION-ENHANCED DELIVERY OF SMALL MOLECULE DRUGS FOR H3 K27-ALTERED DIFFUSE MIDLINE GLIOMA
Authors: Julian Rechberger, Jacob Anderson, Jizhi Ge, Liang Zhang, David Daniels
Journal: Neuro-Oncology (2023)

Abstract H3 K27-altered diffuse midline gliomas (DMG) are uniformly lethal tumors for which no therapy has been found to be effective. The blood-brain barrier (BBB) restricts uptake and accumulation of systemically administered drugs in the brain. Convection-enhanced delivery (CED) circumvents the BBB by directly infusing therapeutics into the tumor, facilitating homogenous distribution of drugs at high local concentrations with minimal systemic toxicity. However, most drugs given by CED are rapidly cleared from the brain, severely limiting its therapeutic potential. Here, we determine the impact of drug characteristics rather than mechanism of action on compatibility with CED. Various medicinal chemistry prediction models were interrogated to define drug categories predicated on inherent physicochemical properties of the drugs. A panel of FDA-approved drugs with biologically validated activity in DMG were selected for each group: panobinostat/ponatinib, everolimus/topotecan, tolnaftate/tretinoin, and carmofur/eltrombopag. In vivo pharmacokinetic studies of these drugs delivered by CED into the pons of tumor-naïve mice showed that drugs expected to be less likely to undergo active efflux persisted at the site of infusion over prolonged periods of time. Conversely, efflux transporter (ET) substrate drugs were quickly excreted from the brain and readily detectable in the plasma following CED. Based on the observed brain and plasma concentration-time profiles, the brain exit rate constant and clearance out of the brain were much higher for ET substrate drugs compared with ET non-substrates, resulting in a significant increase in the residence time (the time spent by drugs in the brain) in the absence of ET-mediated clearance. These properties were further validated in efficacy studies in DMG animal models. The proclivity of many drugs to be rapidly effluxed from the brain after CED generates a vulnerability that can be exploited for the development of novel therapeutic regimens, such as with pharmacokinetics-informed drug selection or concomitant dosing of ET-inhibiting drugs.
BIOM-46. STANDARDIZATION OF LIQUID BIOPSY FOR PEDIATRIC DIFFUSE MIDLINE GLIOMA USING DDPCR
Authors: Daphne Li, Erin Bonner, Tina Huang, Carl Koschmann, Javad Nazarian, Amanda Saratsis
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND Diffuse midline glioma (DMG) is a highly morbid pediatric brain tumor. Up to 80% of DMGs harbor mutations in histone H3-encoding genes, associated with poor prognosis. We previously showed the feasibility of detecting H3 mutations in circulating tumor DNA (ctDNA) in the liquid biome of children diagnosed with DMG. However, detection of low levels of ctDNA is highly dependent on platform sensitivity and sample type. To address this, we optimized ctDNA detection sensitivity and specificity across two commonly used digital droplet PCR (ddPCR) platforms (RainDance and BioRad), and validated methods for detecting H3F3A c.83A &amp;gt;T (H3.3K27M) mutations in DMG CSF, plasma, and primary tumor specimens across three different institutions. METHODS DNA was extracted from H3.3K27M mutant and H3 wildtype (H3WT) specimens, including H3.3K27M tumor tissue (n = 4), CSF (n = 6), plasma (n = 4), and human primary pediatric glioma cells (H3.3K27M, n = 2; H3WT, n = 1). ctDNA detection was enhanced via PCR pre-amplification and use of distinct custom primers and fluorescent LNA probes for c.83 A &amp;gt;T H3F3A mutation detection. Mutation allelic frequency (MAF) was determined and validated through parallel analysis of matched H3.3K27M tissue specimens (n = 3). RESULTS We determined technical nuances between ddPCR instruments, and optimized sample preparation and sequencing protocols for H3.3K27M mutation detection and quantification. We observed 100% sensitivity and specificity for mutation detection in matched DMG tissue and CSF across assays, platforms and institutions. CONCLUSION ctDNA is reliably and reproducibly detected in the liquid biome using ddPCR, representing a clinically feasible, reproducible, and minimally invasive approach for DMG diagnosis, molecular subtyping and therapeutic monitoring.
STEM-03. TARGETING ANDROGEN SIGNALING IN GLIOBLASTOMA
Authors: Sofia Mason, Sylvia Chung, Beatriz Perez San Juan, Hao-Wen Sim, Rachel Dear, Bryan Day, Jeff Holst, Christine Chaffer
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND Glioblastoma is a lethal brain cancer. Androgen receptor (AR) transcript levels and protein expression are upregulated in glioblastoma compared to normal brain. AR signaling has a role in cancer stem cell function in various cancers. Stem cell activity and cancer cell plasticity represent a key resistance mechanism in glioblastoma. Thus, potent brain-penetrant anti-androgen therapies have the potential to improve treatment outcomes in glioblastoma. METHODS Clinical samples and patient derived xenografts were assessed for AR expression by immunohistochemistry. Cytoplasmic AR+ and AR- glioblastoma patient-derived xenografts maintained under stem cell conditions were tested in vitro for their response to anti-androgen therapies (abiraterone, enzalutamide and seviteronel). Stem cell function was assessed using a tumoursphere assay. Changes in plasticity markers, including ZEB1, were measured with immunofluorescence. RESULTS ~55% of people with glioblastoma have detectable cytoplasmic AR based on immunohistochemistry. AR-positive patient-derived glioma stem cell line RN1 was inhibited by low concentrations of anti-androgen agents, with seviteronel having the lowest half maximal inhibitory concentration (IC50) (at 96 hours: enzalutamide 52µM, abiraterone 12µM, seviteronel 7µM). AR-negative line WK1 was also inhibited though with higher IC50s (at 96 hours: enzalutamide 63µM, seviteronel 21µM). Conventional cell lines U87 and U251 were also inhibited by anti-androgen monotherapy. Tumoursphere assays demonstrated that anti-androgen agents inhibit the tumour-forming ability of cells, with seviteronel and abiraterone showing more inhibition than enzalutamide. Immunofluorescence analysis showed downregulation of plasticity marker ZEB1 with anti-androgen treatment (normalised mean fluorescent intensity: abiraterone 0.84, enzalutamide 0.91, seviteronel 0.74). CONCLUSIONS Glioblastoma is a devastating disease, lacking effective or targeted treatments. Targeting AR with repurposed anti-androgen drugs may be a promising therapeutic strategy, with the potential to abrogate treatment resistance. We are now evaluating these anti-androgen regimens in animal experiments, which will provide a more replicative microenvironment and confirm blood-brain barrier penetrance.
BIOM-34. NON-NEOPLASTIC PLASMA EV SUBPOPULATIONS CORRELATE WITH TUMOR SIZE AND OVERALL SURVIVAL IN GLIOBLASTOMA INDEPENDENT OF STEROID USAGE
Authors: Abudumijiti (Zack) Aibaidula, Megan Bauman, Abdul Karim Ghaith, Samantha Bouchal, Ian Parney
Journal: Neuro-Oncology (2023)

Abstract INTRODUCTION Extracellular Vesicles (EVs) are lipid bilayer particles present in almost all biofluids and carry tumor-specific molecular cargo. Plasma EVs are promising sources of biomarker discovery for glioblastoma (GBM). The clinical relevance of non-neoplastic plasma EVs in GBM remains unclear. In this study, we determine if associations exist between plasma EV subpopulation frequencies in GBM and clinical factors. METHODS Platelet-free plasma samples of 63 GBM, 43 Grade 2 glioma, and 45 healthy donors were included. All glioma plasma samples were collected before surgery. Plasma EV subpopulation frequency based on surface expression of EV-associated tetraspanins (CD9/CD81/CD63) and markers of cell origin (CD45/CD41a/CD11b/CD31) was determined by spectral flow cytometry. Clinical information including age, surgery, MGMT methylation status, corticosteroid usage, tumor volume, and overall survival data was recorded. RESULTS Compared to normal donors, GBM patients had increased CD9+, CD63+, CD81+, and CD11b+ EVs but decreased CD41a+ EVs. GBM patients also had the highest frequency of myeloid-derived CD9+CD11b+ EVs (20.17%) followed by grade 2 gliomas (13.78%) and normal donors (2.76%, p&amp;lt; 0.001). More GBM patients (29/63, 46.0%) received preoperative corticosteroids than grade 2 glioma patients (9/43, 20.9%; p = 0.008). Corticosteroid use was not associated with differences in EV subpopulation frequencies in GBM or grade 2 glioma patients. Pearson correlation analysis showed weak but statistically significant correlations between GBM total tumor volume and CD9+ EVs (p = 0.014), CD41a+ EVs (p = 0.037), and CD9+/CD63-/CD81- EVs (p = 0.007). In GBM patients, younger age (&amp;lt; 60 yrs, p = 0.01), gross total resection (p = 0.02), MGMT methylation (p = 0.002), high CD9+ EV expression (p = 0.011), low CD9+CD63-CD81- EV expression (p = 0.009) and low CD9+CD11b+ EV expression (p = 0.006) correlated with longer overall survival. CONCLUSION Differentially expressed non-neoplastic plasma EV subpopulations have significant clinical relevance in GBM including association with tumor volume and predicting survival. Validation of those markers in larger cohorts could reveal new prognostic biomarkers for GBM.
NIMG-22. COMPARISON OF NON-INVASIVE, ML-GENERATED WHOLE-BRAIN SPATIAL RADIOPATHOMIC MAPS DERIVED FROM ANATOMICAL AND DIFFUSION-WEIGHTED MRI ON PATIENTS WITH NEWLY DIAGNOSED-GLIOMA
Authors: Oluwaseun Adegbite, Nate Tran, Annette Molinaro, Joanna Phillips, Peter LaViolette, Samuel Bobholz, Jacob Ellison, Yan Li, Tracy Luks, Anny Shai, Devika Nair, Javier Villanueva-Meyer, Jennifer Connelly, Mitchel Berger, Shawn Hervey-Jumper, Manish Aghi, Susan Chang, Janine Lupo
Journal: Neuro-Oncology (2023)

Abstract INTRODUCTION Spatial heterogeneity in the glioma microenvironment is difficult to capture through singular biopsy samples. Identification of malignant tumor regions can help guide diagnosis and treatment planning. This study compares radiopathomic maps from 2 strategies derived from anatomical and diffusion-weighted MRI: 1) a support vector machine model trained on an MRI dataset with tissue samples of known spatial coordinates to generate spatial maps of probability of KI-67 and cellularity, and 2) a bagged random-forest model derived from 40+ person glioma brain bank of autopsy tissue coregistered to end-of-life MRI to generate spatial maps of cellularity and tumor probability (TPM). We hypothesize that TPMs from autopsy samples will correlate with KI-67 predictions, while cellularity values among methods will correlate. METHODS Spatial maps of tumor pathology from autopsy- and tissue sample-based models were generated on 55 patients newly-diagnosed with glioblastoma that were scanned with anatomical, diffusion-weighted, and metabolic imaging. Mean values were extracted from each map within the T2-hyperintense, non-enhancing lesion (NEL), the contrast-enhancing lesion (CEL), normal-appearing white matter (NAWM), and 5mm diameter spheres centered at the location where tissues were taken. Spearman correlation analysis was used to elucidate the strength of the linear relationship within the selected regions between the two maps. RESULTS Correlations between KI-67 and TPM values were highest and most significant at the tissue sample locations and CEL (ρ=0.306, p=0.002 and ρ=0.312, p=0.044 respectively). Cellularity maps generated from the autopsy-based model showed no significant correlation with newly diagnosed cellularity values at tissue sample locations, potentially highlighting the influence of treatment. CONCLUSION This study examines the current state of ML-generated spatial mapping, highlighting similarities within CEL, but need to account for the effects of subsequent treatment and progression when comparing tumor beyond the CEL between models derived between different time points.
DISP-13. ENHANCING HISPANIC PARTICIPATION IN BRAIN TUMOR TRIALS
Authors: Dalissa Tajera, Irene Marino, Geoffrey De Gennaro, Adriana Martinez, Leonela Wright, Jonathan Trent, Macarena de la Fuente
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND Hispanics represent 18.9% of the U.S. population, 26.8% of Florida population, and is the fastest growing ethnicity in the country. Hispanic representation in clinical trials remains extremely low at less than 3%. Increasing the Hispanic participation rate in clinical trials has been a priority for the University of Miami (UM), who has implemented various initiatives to improve diversity and inclusion of underrepresented ethnic minorities (URM) within our clinical trials, especially brain tumor trials. Efforts such as community outreach raising awareness of clinical trials, translation of informed consents to Spanish, use of bilingual staff trained in cultural communication diversity and inclusion, dedicated social workers and community seminars have played a crucial role at enhancing Hispanic participation within our brain tumor studies. Method Retrospective review using UM’s clinical trial registry to analyze demographics of brain tumor patients consented to therapeutic/non-therapeutic trials between May 2017 to May 2023. RESULTS A total of 431 patients were consented of which 313 (72.4%) actively participated in therapeutic/non-therapeutic trials and 118 (25.1%) screened-failed. Of the accrued participants, 283 (90.42%) self-identified as White, 16 (5.11%) Black/African American, 5 (1.60%) more than one race, 4 (1.28%) Asian, 4 (1.28%) unknown/unreported and 1 (0.32%) American Indian/Alaskan Native. For ethnicity, 160 (51.12%) self-identified as Hispanic/Latino, 148 (47.28%) as non-Hispanic, and 5 (1.60%) were unknown/unreported. 143 (45.69%) were females and 170 (54.31%) were males. For age, 43 (13.73%) were 18-39, 191 (61.02%) 40-64 and 79 (25.24%) were 65 and over. CONCLUSION There is extensive evidence that patients from URM’s groups may not be afforded the same opportunity to participate in clinical trials and thus benefit from advanced therapies offered via them. Efforts to ensure meaningful representations of Hispanics in our brain tumor trials have led to a high accrual rate of Hispanics above national norms to better represent our community's demographics.
DISP-14. THE ASSOCIATION BETWEEN MEDICAID ENROLLMENT CONTINUITY AND CHILDHOOD, ADOLESCENT, AND YOUNG ADULT BRAIN TUMOR SURVIVAL
Authors: Kimberly Johnson, Derek Brown, Tess Thompson
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND Disparities in younger cancer patient survival between individuals with Medicaid and private insurance have been reported. To further understand this association for brain tumor survival, we used Surveillance, Epidemiology, and End RESULTS (SEER)-Medicaid-linked data to test two hypotheses: 1) those enrolled in Medicaid have lower brain tumor survival than those not enrolled, and 2) those with discontinuous enrollment in Medicaid around the time of diagnosis have lower survival than those with continuous enrollment. METHODS SEER-Medicaid linked data on individuals diagnosed with a first malignant primary brain cancer between 0 to 39 years from 2006 to 2013 were obtained with follow-up through 2018. Medicaid enrollment was classified as continuous (enrolled six months before through six months after diagnosis) and discontinuous (enrolled non-continuously in the twelve months surrounding the diagnosis month). We used Kaplan-Meier (KM) curves and Cox Proportional Hazards (PH) regression models with SEs clustered on state to evaluate survival differences in association with Medicaid enrollment timing after adjusting for age, race/ethnicity, and a measure of census tract poverty. RESULTS Our analytic dataset included 10,110 children, adolescents, and young adults, including 3,148 brain tumor deaths. Consistently lower survival probabilities over time were observed for those enrolled in Medicaid, particularly those with discontinuous enrollment for both age groups. Higher hazards of death were observed for those enrolled in Medicaid vs. not enrolled (HR0-19 =1.66 95% CI 1.41-1.95; HR20-39=1.38, 95% CI 1.27-1.51) and with discontinuous vs. continuous in Medicaid enrollment (HR0-19 =1.60, 95% CI 1.43-1.81; HR20-39=2.03, 95% CI 1.75-2.36). CONCLUSIONS These results indicate Medicaid enrollment continuity has an impact on the risk of death, with discontinuous enrollment associated with an over two times higher risk of death for young brain tumor patients. These results further support the critical need for consistent health insurance coverage for children, adolescents, and young adults.
NIMG-56. GENERATIVE ADVERSARIAL NETWORKS FOR BRAIN MRI SYNTHESIS: IMPACT OF TRAINING SET SIZE ON CLINICAL APPLICATIONS
Authors: Marc Zoghby, Bradley Erickson, Gian Marco Conte
Journal: Neuro-Oncology (2023)

Abstract Incomplete MRI exams reduce the possibility of applying AI models. We previously trained two generative adversarial networks (GANs) on 135 subjects from the BraTS-2017 dataset to generate T1 from post-contrast T1 and FLAIR from T2 sequences (baseline models). To test the impact of the training set size, here, we trained the same models using 1251 subjects from the BraTS-2021 dataset. We used the same architecture and hyperparameters from the baseline models: batch size of 1, learning rate 2x10-4, Adam optimizer, cross-entropy and L1-loss. We trained two versions of the updated models: one stopped at an early checkpoint (early models) and one after 50 epochs (late models). We tested all models on institutional MRIs from 487 IDH-wt gliomas. Synthetic MRIs were compared to the originals using the structural-similarity-index (SSI) and MSE. We simulated scenarios where either the T1, FLAIR, or both were missing and used their synthetic version as inputs of a segmentation model. We compared the segmentations using the dice score (DSC) and used Friedman and Dunn’s test to compare the scores and correct for multiple comparisons. Median SSI for the T1 were 0.957, 0.947, 0.947, and median MSE were 0.006, 0.014, 0.008 for the baseline, early, and late models. For the FLAIR, median SSI were 0.924, 0.908, 0.915, and median MSE were 0.016, 0.016, 0.019 for the baseline, early, and late models. The DSC ranges for the baseline and updated models were (0.655 - 0.953), (0.420 - 0.952), and (0.610 - 0.952). The baseline and late models showed no statistically significant differences in DSC, but both performed significantly better than the early models. We show that GANs trained to synthesize brain MRIs on a small cohort perform similarly to those trained on an x10-larger cohort, making them a viable option for rare diseases or institutions with limited resources.